乔剑博，山东大学软件学院人工智能方向博士研究生。我于2022年获得山东大学软件工程学士学位，目前在魏乐义教授课题组（WeiLab）攻读博士学位。我的研究兴趣包括人工智能与生物信息学、AI药物发现和基因组序列分析。近年来发表论文30余篇，其中以一作、共一或通讯作者发表论文13篇，如Nature Communications (2025, 2026)、Science China Information Sciences (一区TOP, CCF-A)等领域顶级刊物。相关工作被引用400余次，目前H-因子(Google)为10。

🔥 新闻动态

2026.08: 🎉 一篇论文被Nature Communications接收 [Nature子刊, 一区TOP]。
2026.07: 🎉 一篇论文被Journal of Chemical Theory and Computation接收 [一区TOP]。
2026.07: 🎉 一篇论文被Journal of Chemical Information and Modeling接收。
2026.07: 🎉 一篇论文被ACS Synthetic Biology接收。
2026.06: 🤗 获山东大学学术之星·优秀成果奖。
2026.05: 🎉 一篇论文被Journal of Cheminformatics接收 [一区TOP]。
2025.12: 🎉 一篇论文被ACS Synthetic Biology接收。
2025.10: 一篇论文被Computational Biology and Chemistry接收。
2025.10: 🤗 获研究生国家奖学金。
2025.08: 一篇论文被Methods接收。
2025.05: 🎉 一篇论文被Science China Information Sciences接收 [一区TOP, CCF-A]。
2025.05: 🎉 一篇论文被Neural Networks接收 [一区TOP, CCF-B]。
2025.04: 🎉 一篇论文被Nature Communications接收 [Nature子刊, 一区TOP]。
2024.01: 🎉 一篇论文被Information Sciences接收 [一区TOP, CCF-B]。

📖 教育经历

2022.09 - 至今，山东大学，人工智能，博士研究生
2018.09 - 2022.06，山东大学，软件工程，学士

📝 学术论文

Nat. Commun.

A self-conformation-aware pre-training framework for molecular property prediction with substructure interpretability.
Jianbo Qiao#, Junru Jin#, Ding Wang#, Saisai Teng, Junyu Zhang, Xuetong Yang, Yuhang Liu, Yu Wang, Lizhen Cui, Quan Zou, Ran Su, Leyi Wei. Nature Communications, 2025. [Nature子刊, 一区TOP].

Nat. Commun.

Decoding the Sequence Determinants of Locus Specific DNA Methylation Across Human Tissues.
Junru Jin#, Ding Wang#, Jianbo Qiao#, Wenjia Gao, Yuhang Liu, Siqi Chen, Quan Zou, Shu Wu, Ran Su, Leyi Wei. Nature Communications, 2026. [Nature子刊, 一区TOP].

Sci. China Inf. Sci.

Molecular pretraining models towards molecular property prediction.
Jianbo Qiao, Wenjia Gao, Junru Jin, Ding Wang, Xu Guo, Balachandran Manavalan, Leyi Wei. Science China Information Sciences, 2025. [一区TOP, CCF-A].

J. Chem. Theory Comput.

Relation-Aware Pretraining and Reaction Center Modeling for Chemical Reaction Graph Representation Learning.
Jianbo Qiao#, Kefei Li#, Junru Jin, Ding Wang, Wenjia Gao, Shaoye Zhang, Shuan Liu, Leyi Wei. Journal of Chemical Theory and Computation, 2026. [一区TOP].

Neural Netw.

Taco-DDI: accurate prediction of drug-drug interaction events using graph transformers and dynamic co-attention matrices.
Jianbo Qiao, Xu Guo, Junru Jin, Ding Wang, Kefei Li, Wenjia Gao, Feifei Cui, Zilong Zhang, Hua Shi, Leyi Wei. Neural Networks, 2025. [一区TOP, CCF-B].

Inf. Sci.

Towards retraining-free RNA modification prediction with incremental learning.
Jianbo Qiao, Junru Jin, Haoqing Yu, Leyi Wei. Information Sciences, 2024. [一区TOP, CCF-B].

FGSGT-DDI: LLM-Enhanced Functional Group Semantic Graph Transformer for Drug–Drug Interaction Prediction.
Kefei Li#, Jianbo Qiao#, Yuntao Yang, Hanjun Zhao, Ding Wang, Junru Jin, Zhongmin Yan, Leyi Wei. Journal of Chemical Information and Modeling, 2026.
An Explainable Deep Learning Framework Integrating DNA Sequence and Transcription Initiation Signals for Gene Expression Prediction.
Jianbo Qiao#, Wenjia Gao#, Ding Wang#, Junru Jin#, Siqi Chen, Zhongmin, Yan, Leyi Wei. ACS Synthetic Biology, 2026.
CataCon: a contrastive graph representation learning framework for catalyst prediction.
Hua Shi, Yuzhe Wang, Shouzhen Song, Kefei Li, Wenjia Gao, Shuan Liu, Jianbo Qiao*, Leyi Wei*. Journal of Cheminformatics, 2026. [一区TOP].
FGMA: A Functional Group-enhanced Deep Learning Method for Drug Toxicity Prediction.
Yue Cheng#, Jianbo Qiao#, Siqi Chen, Leyi Wei, Guangmin Liang. Current Drug Targets, 2026.
ABT-DDI: A Graph Transformer Model with Atomic-Bond Structure Awareness for Drug–Drug Interaction Prediction.
Xu Guo#, Jianbo Qiao#, Siqi Chen, Junru Jin, Ding Wang, Wenjia Gao, Feifei Cui, Zilong Zhang, Hua Shi, Zhongmin Yan, Leyi Wei, Xinbo Jiang. ACS Synthetic Biology, 2025.
TK-DDI: Accurate and efficient drug-drug interaction prediction via token encoding.
Yue Cheng#, Jianbo Qiao#, Siqi Chen, Leyi Wei, Guangmin Liang. Computational Biology and Chemistry, 2025.
Efficient RNA nucleotide encoding enhances the accurate prediction of ac4C modifications.
Na Li*, Xiao Wang, Ming Zeng, Feng Cao, Ke Qiu, Jianbo Qiao*. Methods, 2025.

A Token-Pruning Framework Enables Efficient Representation of the Human Genome for RNA Modification Analysis.
Wenjia Gao, Junlei Yu, Junru Jin, Jiajie Cai, Ke Qiu, Shun Zhang, Jianbo Qiao, Leyi Wei. Bioinformatics, 2026. [CCF-A].
Hyp-retro: hypernetwork-guided preference-conditioned retrosynthetic planner.
Jingwen Wang, Shuan Liu, Shaoye Zhang, Jianbo Qiao, Guanhe Li, Hanjun Zhao, Xiangxiang Zeng, Jinjin Li, Changhang Lin, Chen Su, Leyi Wei. Molecular Diversity, 2026.
PeptideSGCL: Structure-enhanced graph-transformer encoding and dual-level contrastive learning for peptide property prediction.
Jiajie Cai, Shuwen Xiong, Yuntao Yang, Hanjun Zhao, Jianbo Qiao, Zhongmin Yan, Ran Su, Xinbo Jiang, Lichao Zhang, Leyi Wei. ACS Synthetic Biology, 2026.
CMA-Nano: A DNA Methylation Detection Method for Nanopore Sequencing Data Based on a Cross-Modal Attention Mechanism.
Hua Shi, Chenglin Yin, Jianbo Qiao, Wenjia Gao, Leyi Wei. ACS Omega, 2026.
Accurate and interpretable ADMET prediction: Integrating structural, geometric, and global molecular context representations.
Ke Qiu, Kefei Li, Jianbo Qiao, Ding Wang, Junru Jin, Zhongmin Yan, Ka-Chun Wong, Leyi Wei. European Journal of Medicinal Chemistry, 2026.
Structure-Aware Multimodal Learning Improves Minor-Class Signal Peptide Prediction.
Yuntao Yang, Shuwen Xiong, Siqi Chen, Jianbo Qiao, Hanjun Zhao, Zhongmin Yan, Leyi Wei. ACS Synthetic Biology, 2026.
HGCPep: Hypergraph Deep Learning Identifies Cancer-associated Non-coding Peptides.
Wentao Long, Zhongshen Li, Junru Jin, Jianbo Qiao, Yu Wang, Leyi Wei. Genomics, Proteomics & Bioinformatics, 2025. [一区TOP].
Accurate detection and quantification of single-base m6A RNA modification using nanopore signals with multi-view deep learning.
Jun Zhang, Jianbo Qiao, Zhiqun Zhao, Chenglin Yin, Junru Jin, Ding Wang, Wenjia Gao, Leyi Wei. bioRxiv, 2025.
MCAMEF-BERT: an efficient deep learning method for RNA N7-methylguanosine site prediction via multi-branch feature integration.
Junlei Yu, Wenjia Gao, Siqi Chen, Ronglin Lu, Jianbo Qiao, Junru Jin, Leyi Wei, Hua Shi, Zilong Zhang, Feifei Cui, Xinbo Jiang, Zhongmin Yan. Briefings in Bioinformatics, 2025. [二区TOP, CCF-B].
EDNTOM: An Ensemble Learning and Weight Mechanism-Based Nanopore Methylation Detection Tool.
Ge Tian, Chenglin Yin, Jianbo Qiao, Ruheng Wang, Hua Shi, Feifei Cui, Zilong Zhang, Xinbo Jiang, Leyi Wei. ACS Omega, 2025. [二区TOP].
GICL: A Cross-Modal Drug Property Prediction Framework Based on Knowledge Enhancement of Large Language Models.
Na Li, Jianbo Qiao, Fei Gao, Yanling Wang, Hua Shi, Zilong Zhang, Feifei Cui, Lichao Zhang, Leyi Wei. Journal of Chemical Information and Modeling, 2025. [二区TOP].
MC-MSTLoc: Self-supervised Pre-training for Imbalanced Multi-label Protein Subcellular Localization Prediction Using Immunofluorescence Images.
Fengsheng Wang, Jianbo Qiao, Xu Guo, Leyi Wei. IEEE Transactions on Computational Biology and Bioinformatics (TCBB), 2025. [CCF-B].
Computational models for prediction of m6A sites using deep learning.
Nan Sheng, Jianbo Qiao, Leyi Wei, Hua Shi, Huannan Guo, Changshun Yang. Methods, 2025.
ERNIE-ac4C: A novel deep learning model for effectively predicting N4-acetylcytidine sites.
Ronglin Lu, Jianbo Qiao, Kefei Li, Yanxi Zhao, Junru Jin, Feifei Cui, Zilong Zhang, Balachandran Manavalan, Leyi Wei. Journal of Molecular Biology, 2025.
Moss-m7G: A motif-based interpretable deep learning method for RNA N7-methlguanosine site prediction.
Yanxi Zhao, Junru Jin, Wenjia Gao, Jianbo Qiao, Leyi Wei. Journal of Chemical Information and Modeling, 2024. [二区TOP].
NanoCon: contrastive learning-based deep hybrid network for nanopore methylation detection.
Chenglin Yin, Ruheng Wang, Jianbo Qiao, Hua Shi, Hongliang Duan, Xinbo Jiang, Saisai Teng, Leyi Wei. Bioinformatics, 2024. [CCF-A].
Multi-CGAN: deep generative model-based multiproperty antimicrobial peptide design.
Haoqing Yu, Ruheng Wang, Jianbo Qiao, Leyi Wei. Journal of Chemical Information and Modeling, 2023. [二区TOP].
Deep Generative Models in De Novo Drug Molecule Generation.
Chao Pang, Jianbo Qiao, Xiangxiang Zeng, Quan Zou, Leyi Wei. Journal of Chemical Information and Modeling, 2023. [二区TOP].
Rm-LR: a long-range-based deep learning model for predicting multiple types of RNA modifications.
Sirui Liang, Yanxi Zhao, Junru Jin, Jianbo Qiao, Ding Wang, Yu Wang, Leyi Wei. Computers in Biology and Medicine, 2023.
Clinical Phenotyping Prediction via Auxiliary Task Selection and Adaptive Shared-Space Correction.
Xiao Yang, Ning Liu, Jianbo Qiao, Haitao Yuan, Teng Ma, Yonghui Xu, Lizhen Cui. CAAI International Conference on Artificial Intelligence (CICAI), 2022.

🎖 荣誉奖励

2026.06 获山东大学学术之星·优秀成果奖。
2025.10 获研究生国家奖学金。

💬 邀请报告

无需重新训练的RNA修饰预测增量学习方法。第二届 CCF 生物信息学“新未来”青年学者（BIO-3NEW）研讨会，2024.04。

✏️ 学术服务

专题协调人

Frontiers in Neurology. 参见我们的 Research Topic

会议审稿人

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

期刊审稿人

IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
Engineering Applications of Artificial Intelligence (EAAI)
IEEE Journal of Biomedical and Health Informatics (JBHI)
Molecular Diversity
Scientific Reports
Chemical Papers
International Journal of Data Science and Analytics
BMC Bioinformatics
BMC Medical Genomics
BMC Artificial Intelligence
Journal of King Saud University Computer and Information Sciences
Discover Applied Sciences
In Silico Pharmacology